The statements in this section merely provide background information related to the present disclosure and do not constitute prior art.
Haze is an atmospheric phenomenon of water vapor floating in the form of condensed droplets. Hazy environment typically causes an obstruction to vision of less than 1 km of visibility. Such foggy weather causes particulate water droplets and in turn scattering of light. The scattering of light represents directional changes of traveling light as it collides with airborne particles. The scattering depends on the wavelength of light and the particle size.
Light scattering is generally divided into Rayleigh scattering and Mie scattering. The Rayleigh scattering applies when the size of the particles that cause the scattering is smaller than the wavelength of light where the scattering energy is inversely proportional to the fourth power of the wavelength. This is exemplified by blue hue of the sky in a sunny day when air molecules scatter the light by scattering more blue than red. However, the Mie scattering theory applies to the light scattering when the size of the responsible particles is greater than the wavelength of light. Haze follows the Mie scattering theory since the particles of haze have the diameter as large as a few μm to a few tens of μm over the wavelength of 400 nm˜700 nm of visible light. According to the Mie scattering theory, with larger scattering particles like water droplets in the atmosphere, the amount of scattering is less influenced by the wavelength to cause near-even scattering of all the light in the visible light zone. Thus, when the condition is hazy, objects exhibit a blurred image. At this time, a new light source called airlight is generated.
The inventor(s) has noted that image quality improvement through correction of the haze distortion resolve the visibility obstruction and sharpen fuzzy images. In addition, the inventor(s) has noted that such image improvement is important as a pre-processing step for recognition of the objects by restoring damaged information on letters, objects, and the like due to the haze.
Known dehazing technologies are roughly categorized into a non-model approach and a model approach.
An example of the non-model approach includes histogram equalization. The histogram equalization is a method for analyzing a histogram of an image to adjust distribution. The inventor(s) has experienced that The histogram equalization is easy and provides an improved effect but is not proper for a hazy image having a non-uniform depth. In addition, the inventor(s) has experienced that the histogram equalization is proper for improving general image quality but does not satisfactorily reflect characteristics of an influence that haze has on an image. The inventor(s) has experienced that for an image containing thick haze, it provides an insignificant improvement.
The model approach is for modeling an influence that a scattering phenomenon of light due to haze has on an image. The inventor(s) has noted that first, a technology has been disclosed for comparing two or more images obtained in different weathers to estimate and correct a scene depth, thereby correcting distortion due to haze. However, the inventor(s) has experienced that in this technology, input of at least two images under different weathers is required. For a real-time implementation, therefore, The inventor(s) has experienced that it is necessary to monitor weather changes and provide a commensurate image storage space thereto. In addition, the inventor(s) has experienced that it is difficult to determine a storage period since a weather change cycle cannot be estimated. Furthermore, the inventor(s) has noted that it is necessary to capture the same scene having no error. Therefore, the inventor(s) has noted that a moving object frequently causes an error during estimation of the degree of haze distortion.
Next, the inventor(s) has noted that there is a known technology for correcting distortion due to haze by estimating and subtracting the amount of change of pixel values of an image due to the haze. The inventor(s) has noted that this technology is based on the assumption that the haze is uniform, which is only applicable to uniform and thin haze. However, the inventor(s) has noted that most real world haze tends to be non-uniform. The inventor(s) has experienced that even to uniform haze, this method has disadvantage because the degree of the haze influence depends on the distance between a camera and an object.